diff --git a/src/Agent/AgentRunner.php b/src/Agent/AgentRunner.php
index 109a2cf..6b06913 100644
--- a/src/Agent/AgentRunner.php
+++ b/src/Agent/AgentRunner.php
@@ -20,37 +20,39 @@ final readonly class AgentRunner
private bool $systemMsgOn;
public function __construct(
- private PromptBuilder $promptBuilder,
- private ThinkSuppressor $thinkSuppressor,
- private ContextService $contextService,
- private UrlAnalyzer $urlAnalyzer,
+ private PromptBuilder $promptBuilder,
+ private ThinkSuppressor $thinkSuppressor,
+ private ContextService $contextService,
+ private UrlAnalyzer $urlAnalyzer,
private RetrieverInterface $retriever,
- private ShopSearchService $shopSearchService,
+ private ShopSearchService $shopSearchService,
private CommerceIntentLite $commerceIntentLite,
- private OllamaClient $ollamaClient,
- private LoggerInterface $agentLogger,
- private AgentRunnerConfig $agentRunnerConfig,
- private bool $debug,
- private bool $logPrompt,
- private bool $logContext,
- )
- {
+ private OllamaClient $ollamaClient,
+ private LoggerInterface $agentLogger,
+ private AgentRunnerConfig $agentRunnerConfig,
+ private bool $debug,
+ private bool $logPrompt,
+ private bool $logContext,
+ ) {
$this->systemMsgOn = true;
}
- public function run(string $prompt, string $userId, ?bool $includeFullContext = false): Generator
+ public function run(string $prompt, string $userId, bool $includeFullContext = false): Generator
{
$prompt = trim($prompt);
- $swagFullOutPut = '';
- $firstThinkLoop = true;
- $shopResults = [];
- $sources = [];
if ($prompt === '') {
- yield '❌ Empty prompt.';
+ yield $this->systemMsg('❌ Empty prompt.', 'err');
return;
}
+ $urlContent = '';
+ $knowledgeChunks = [];
+ $shopResults = [];
+ $sources = [];
+ $optimizedShopQuery = '';
+ $commerceIntent = CommerceIntentLite::NONE;
+
$this->agentLogger->info('Agent run started', [
'userId' => $userId,
]);
@@ -59,95 +61,63 @@ final readonly class AgentRunner
// ---------------------------------------------------------
// 1) Context strategy
// ---------------------------------------------------------
-
if ($includeFullContext) {
- //Coming soon
+ // Full context mode is already passed to PromptBuilder.
+ // Additional context strategies can be added here later.
}
- yield $this->systemMsg("Ich analysiere deine Anfrage...", "think");
+ yield $this->systemMsg('Ich analysiere deine Anfrage...', 'think');
// ---------------------------------------------------------
- // 2) Extract URL content (if present)
+ // 2) Extract URL content
// ---------------------------------------------------------
- yield $this->systemMsg("Ich prüfe auf Internet Quellen...", "think");
+ yield $this->systemMsg('Ich prüfe auf Internetquellen...', 'think');
+
$urlContent = $this->urlAnalyzer->extractContentFromPrompt($prompt);
- if($urlContent){
- $sources[]= 'Externe URL';
+ if ($urlContent !== '') {
+ $this->addSource($sources, 'Externe URL');
}
// ---------------------------------------------------------
// 3) Retrieve RAG knowledge
// ---------------------------------------------------------
- yield $this->systemMsg("Ich hole relevante Daten aus meinem RAG Wissen...", "think");
+ yield $this->systemMsg('Ich hole relevante Daten aus meinem RAG-Wissen...', 'think');
+
$knowledgeChunks = $this->retriever->retrieve($prompt);
- if($knowledgeChunks){
- $sources[]= 'RAG Wissen';
+ if ($knowledgeChunks !== []) {
+ $this->addSource($sources, 'RAG Wissen');
}
+
// ---------------------------------------------------------
- // 4) commerce/shop search
+ // 4) Optional commerce/shop search
// ---------------------------------------------------------
+ $commerceIntent = $this->detectCommerceIntent($prompt);
- $commerceMeta = $this->commerceIntentLite->detect($prompt);
- $commerceIntent = (string)($commerceMeta['intent'] ?? CommerceIntentLite::NONE);
+ if ($this->isCommerceIntent($commerceIntent)) {
+ yield $this->systemMsg('Ich optimiere die Recherche...', 'think');
- if ($commerceIntent === CommerceIntentLite::PRODUCT_SEARCH || $commerceIntent === CommerceIntentLite::ADVISORY_PRODUCT_SEARCH) {
- //PreOptimize swag search query
- $promptSwagSearch = $this->agentRunnerConfig->getShopPrompt($prompt);
+ $optimizedShopQuery = $this->buildOptimizedShopQuery($prompt, $userId);
+ $shopSearchQuery = $optimizedShopQuery !== '' ? $optimizedShopQuery : $prompt;
- //Reset thinkSuppressor
- $this->thinkSuppressor->reset();
+ yield $this->systemMsg(
+ 'Ich rufe Recherchedaten ab (type: ' . $commerceIntent . ')',
+ 'think'
+ );
- yield $this->systemMsg("Ich optimere die Recherche...", "think");
+ $shopResults = $this->searchShop($shopSearchQuery, $commerceIntent, $userId);
- //Call AI for optimized swag query
- foreach ($this->ollamaClient->stream($promptSwagSearch) as $swagToken) {
-
- if (!is_string($swagToken)) {
- continue;
- }
-
- $swagCleanToken = $this->thinkSuppressor->filter($swagToken);
-
- if ($swagCleanToken === '') {
- continue;
- }
-
- $swagFullOutPut .= $swagCleanToken;
- }
-
- yield $this->systemMsg("Ich rufe Recherchedaten ab (type: " . $commerceIntent . ")", "think");
-
- //Search in swag by AI optimized query
- try {
- $shopResults = $swagFullOutPut !== ''
- ? $this->shopSearchService->search($swagFullOutPut, $commerceIntent)
- : [];
- } catch (Throwable $e) {
- $this->agentLogger->warning('Shop search failed, continuing without shop results', [
- 'userId' => $userId,
- 'exception' => $e,
- ]);
-
- yield $this->systemMsg('Shopdaten konnten nicht geladen werden, ich antworte mit Wissensbasis weiter...', 'think');
+ if ($shopResults !== []) {
+ $this->addSource($sources, 'Shopsystem');
}
}
- if($shopResults){
- $sources[]= 'Shopsystem';
- }
+ $knowledgeChunks = $this->limitKnowledgeChunks($knowledgeChunks, $commerceIntent);
- if ($commerceIntent === CommerceIntentLite::PRODUCT_SEARCH) {
- $knowledgeChunks = array_slice($knowledgeChunks, 0, 2);
- } elseif ($commerceIntent === CommerceIntentLite::ADVISORY_PRODUCT_SEARCH) {
- $knowledgeChunks = array_slice($knowledgeChunks, 0, 3);
- }
-
- yield $this->systemMsg("Ich analysiere alle Informationen...", "think");
+ yield $this->systemMsg('Ich analysiere alle Informationen...', 'think');
// ---------------------------------------------------------
// 5) Build final prompt
// ---------------------------------------------------------
-
$finalPrompt = $this->promptBuilder->build(
prompt: $prompt,
userId: $userId,
@@ -155,15 +125,20 @@ final readonly class AgentRunner
knowledgeChunks: $knowledgeChunks,
shopResults: $shopResults,
fullContext: $includeFullContext,
- swagFullOutPut: $swagFullOutPut
+ swagFullOutPut: $optimizedShopQuery
);
if ($this->debug && $this->logPrompt) {
- $this->agentLogger->debug($finalPrompt);
+ $this->agentLogger->debug('Final prompt', [
+ 'userId' => $userId,
+ 'finalPrompt' => $finalPrompt,
+ 'optimizedShopQuery' => $optimizedShopQuery,
+ ]);
}
if ($this->debug && $this->logContext) {
$this->agentLogger->debug('Conversation context snapshot', [
+ 'userId' => $userId,
'context' => $this->contextService->buildUserContext(
$userId,
$includeFullContext
@@ -171,71 +146,39 @@ final readonly class AgentRunner
]);
}
+ if ($sources !== []) {
+ yield $this->emitSources($sources, 'Genutzte Quellen: ');
+ }
+print'';print_r($finalPrompt);exit;
// ---------------------------------------------------------
- // 6) Stream tokens from the LLM backend (chunked streaming)
+ // 6) Stream final LLM answer
// ---------------------------------------------------------
- $fullOutput = '';
- $chunker = new StreamChunker();
- $chunker->flush();
- $this->thinkSuppressor->reset();
+ $fullOutput = yield from $this->streamFinalAnswer($finalPrompt);
- if($sources){
- yield $this->systemMsg("Genutze Quellen: ".implode(' ',$sources), 'info');
- }
-
- foreach ($this->ollamaClient->stream($finalPrompt) as $token) {
-
- if (!is_string($token)) {
- continue;
- }
-
- $cleanToken = $this->thinkSuppressor->filter((string)$token);
-
- if ($cleanToken === '') {
- if ($firstThinkLoop) {
- yield $this->systemMsg("Denke nach...", "think");
- $firstThinkLoop = false;
- }
- continue;
- }
-
- // Vollständige Antwort weiter sammeln (für History)
- $fullOutput .= $cleanToken;
-
- // ⬇️ Token in Chunker geben
- $chunk = $chunker->push($cleanToken);
- if ($chunk !== null) {
- yield $this->systemMsg($chunk, 'answer');
- }
- }
-
- // ⬇️ Rest flushen
- $finalChunk = $chunker->flush();
- if ($finalChunk !== null) {
- yield $this->systemMsg($finalChunk, 'answer');
- } elseif ($fullOutput === '') {
- yield $this->systemMsg('❌ Es wurden keine Daten vom LLM empfangen.', 'err');
- }
-
- if($sources){
- yield $this->systemMsg("Quellen: ".implode(' ',$sources), 'info');
+ if ($sources !== []) {
+ yield $this->emitSources($sources, 'Quellen: ');
}
// ---------------------------------------------------------
// 7) Persist conversation history
// ---------------------------------------------------------
- $this->contextService->appendHistory(
- $userId,
- $prompt,
- $fullOutput
- );
+ if ($fullOutput !== '') {
+ $this->contextService->appendHistory(
+ $userId,
+ $prompt,
+ $fullOutput
+ );
+ }
$this->agentLogger->info('Agent run finished', [
'userId' => $userId,
'outputLength' => mb_strlen($fullOutput),
- 'contextMode' => 'recent',
+ 'contextMode' => $includeFullContext ? 'full' : 'recent',
'commerceIntent' => $commerceIntent,
'shopResultsCount' => count($shopResults),
+ 'knowledgeChunkCount' => count($knowledgeChunks),
+ 'hasUrlContent' => $urlContent !== '',
+ 'usedOptimizedShopQuery' => $optimizedShopQuery !== '',
]);
} catch (Throwable $e) {
$this->agentLogger->error('Agent run failed', [
@@ -243,10 +186,168 @@ final readonly class AgentRunner
'exception' => $e,
]);
- yield $this->systemMsg("\n❌ An internal error occurred while processing the request. \nError: " . $e->getMessage(), 'err');
+ yield $this->systemMsg($this->buildUserErrorMessage($e), 'err');
}
}
+ private function detectCommerceIntent(string $prompt): string
+ {
+ $commerceMeta = $this->commerceIntentLite->detect($prompt);
+
+ return (string) ($commerceMeta['intent'] ?? CommerceIntentLite::NONE);
+ }
+
+ private function isCommerceIntent(string $commerceIntent): bool
+ {
+ return $commerceIntent === CommerceIntentLite::PRODUCT_SEARCH
+ || $commerceIntent === CommerceIntentLite::ADVISORY_PRODUCT_SEARCH;
+ }
+
+ private function buildOptimizedShopQuery(string $prompt, string $userId): string
+ {
+ $shopPrompt = trim($this->agentRunnerConfig->getShopPrompt($prompt));
+
+ if ($shopPrompt === '') {
+ return '';
+ }
+
+ $optimizedQuery = '';
+ $this->thinkSuppressor->reset();
+
+ try {
+ foreach ($this->ollamaClient->stream($shopPrompt) as $token) {
+ if (!is_string($token)) {
+ continue;
+ }
+
+ $cleanToken = $this->thinkSuppressor->filter($token);
+
+ if ($cleanToken === '') {
+ continue;
+ }
+
+ $optimizedQuery .= $cleanToken;
+ }
+ } catch (Throwable $e) {
+ $this->agentLogger->warning('Shop query optimization failed, falling back to original prompt', [
+ 'userId' => $userId,
+ 'exception' => $e,
+ ]);
+
+ return '';
+ }
+
+ return trim($optimizedQuery);
+ }
+
+ private function searchShop(string $query, string $commerceIntent, string $userId): array
+ {
+ try {
+ return $this->shopSearchService->search($query, $commerceIntent);
+ } catch (Throwable $e) {
+ $this->agentLogger->warning('Shop search failed, continuing without shop results', [
+ 'userId' => $userId,
+ 'commerceIntent' => $commerceIntent,
+ 'query' => $query,
+ 'exception' => $e,
+ ]);
+
+ return [];
+ }
+ }
+
+ private function limitKnowledgeChunks(array $knowledgeChunks, string $commerceIntent): array
+ {
+ return match ($commerceIntent) {
+ CommerceIntentLite::PRODUCT_SEARCH => array_slice($knowledgeChunks, 0, 2),
+ CommerceIntentLite::ADVISORY_PRODUCT_SEARCH => array_slice($knowledgeChunks, 0, 3),
+ default => $knowledgeChunks,
+ };
+ }
+
+ /**
+ * @return Generator
+ */
+ private function streamFinalAnswer(string $finalPrompt): Generator
+ {
+ $fullOutput = '';
+ $firstThinkLoop = true;
+ $chunker = new StreamChunker();
+
+ $this->thinkSuppressor->reset();
+
+ foreach ($this->ollamaClient->stream($finalPrompt) as $token) {
+ if (!is_string($token)) {
+ continue;
+ }
+
+ $cleanToken = $this->thinkSuppressor->filter($token);
+
+ if ($cleanToken === '') {
+ if ($firstThinkLoop) {
+ yield $this->systemMsg('Denke nach...', 'think');
+ $firstThinkLoop = false;
+ }
+
+ continue;
+ }
+
+ $fullOutput .= $cleanToken;
+
+ $chunk = $chunker->push($cleanToken);
+ if ($chunk !== null) {
+ yield $this->systemMsg($chunk, 'answer');
+ }
+ }
+
+ $finalChunk = $chunker->flush();
+ if ($finalChunk !== null) {
+ yield $this->systemMsg($finalChunk, 'answer');
+ } elseif ($fullOutput === '') {
+ yield $this->systemMsg('❌ Es wurden keine Daten vom LLM empfangen.', 'err');
+ }
+
+ return $fullOutput;
+ }
+
+ /**
+ * @param string[] $sources
+ */
+ private function emitSources(array $sources, string $prefix): string
+ {
+ return $this->systemMsg($prefix . implode(' ', $sources), 'info');
+ }
+
+ /**
+ * @param string[] $sources
+ */
+ private function addSource(array &$sources, string $label): void
+ {
+ $badge = $this->badge($label);
+
+ if (!in_array($badge, $sources, true)) {
+ $sources[] = $badge;
+ }
+ }
+
+ private function buildUserErrorMessage(Throwable $e): string
+ {
+ if (!$this->debug) {
+ return '❌ Bei der Verarbeitung der Anfrage ist ein interner Fehler aufgetreten.';
+ }
+
+ return '❌ Interner Fehler: '
+ . htmlspecialchars($e->getMessage(), ENT_QUOTES | ENT_SUBSTITUTE, 'UTF-8');
+ }
+
+ private function badge(string $label): string
+ {
+ return sprintf(
+ '%s',
+ htmlspecialchars($label, ENT_QUOTES | ENT_SUBSTITUTE, 'UTF-8')
+ );
+ }
+
private function systemMsg(string $msg, string $type = ''): string
{
if (!$this->systemMsgOn) {
@@ -254,10 +355,11 @@ final readonly class AgentRunner
}
return match ($type) {
- 'answer' => '' . $msg,
+ 'answer' => $msg,
'err' => '' . $msg . "\n
\n",
'think' => '' . $msg . "\n",
- 'info' => "\n\n" . $msg . "\n"
+ 'info' => "\n\n" . $msg . "\n",
+ default => $msg,
};
}
}
\ No newline at end of file
diff --git a/src/Config/AgentRunnerConfig.php b/src/Config/AgentRunnerConfig.php
index 62bb278..b09ee98 100644
--- a/src/Config/AgentRunnerConfig.php
+++ b/src/Config/AgentRunnerConfig.php
@@ -22,6 +22,7 @@ class AgentRunnerConfig
- Preserve product names, brands, model numbers, and compound terms exactly if they are relevant.
- Numbers that belong to a product name or model must be preserved (e.g. Indikator 300, Testomat 808, Testomat 2000).
- Separate terms using spaces only.
+ - If a relevant product name is present, it must be placed at the beginning of the final search query.
Output format:
Keyword1 Keyword2 Keyword3